Complete stability in multistable delayed neural networks.
We investigate the complete stability for multistable delayed neural networks. A new formulation modified from the previous studies on multistable networks is developed to derive componentwise dynamical property. An iteration argument is then constructed to conclude that every solution of the network converges to a single equilibrium as time tends to infinity. The existence of 3n equilibria and 2n positively invariant sets for the n-neuron system remains valid under the new formulation. The theory is demonstrated by a numerical illustration.
Cheng
Chang-Yuan
CY
Department of Applied Mathematics, National Pingtung University of Education, Pingtung, Taiwan 900, ROC. cycheng@mail.npue.edu.tw
Shih
Chih-Wen
CW
D000818:Animals; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D016571:Neural Networks, Computer; D009474:Neurons / Q000502:physiology*; D017711:Nonlinear Dynamics